I established a foundational understanding of equity research by learning how investing functions and what influences stock prices. I selected a publicly traded company to analyze, laying the groundwork for my investment analysis throughout the externship.

I conducted a thorough review of the company’s financial statements and SEC filings, focusing on 10-K reports and press releases. This analysis enhanced my ability to interpret financial data and identify potential warning signs, crucial for developing a robust investment thesis.

I assessed the competitive landscape, identifying key competitors, risks, and market catalysts that could influence the company’s performance. This analysis provided critical insights into the factors affecting the investment decision.

I developed essential Excel skills for financial modeling, including using formulas and creating charts. I built a comprehensive financial model for my selected company, projecting its performance and calculating key financial ratios to evaluate its potential.

I utilized AI tools such as Perplexity, ChatGPT, and Replit to identify customer frustrations, creating a Pain-Point Chart. This process allowed me to derive actionable insights and engage with peers through critical feedback on their charts, ultimately forming a foundation for a comprehensive

I distinguished between consumers and customers, which informed the creation of an 'Ideal Consumer List' for targeted segments. Using the AIDA framework, I developed a detailed Customer Journey Map that effectively illustrated key touchpoints between the business and consumers.

I analyzed consumer insights derived from survey data, conducting both quantitative and qualitative analyses using advanced methods. This included developing data visualizations in Google Sheets to present findings clearly, culminating in AI-driven analysis that enriched my understanding of

I conducted exploratory data analysis (EDA) and sentiment analysis using Python, including data gathering and cleaning with tools like Pandas and NumPy. I visualized insights derived from customer reviews collected from online sources, enriching the analysis of consumer sentiments.